scholarly journals High-throughput Evaluation of Catalytic Activity by Infrared Thermography

TANSO ◽  
2003 ◽  
Vol 2003 (209) ◽  
pp. 171-173 ◽  
Author(s):  
Hiroshi Shioyame ◽  
Yusuke Yamada ◽  
Yuki Sairyo
Keyword(s):  
Catalytic Activity ◽  
Infrared Thermography ◽  
High Throughput

Directed Evolution of P450 Fatty Acid Decarboxylases via High-Throughput Screening Towards Improved Catalytic Activity

2019 ◽  
Author(s):  
Huifang Xu ◽  
Weinan Liang ◽  
Linlin Ning ◽  
Yuanyuan Jiang ◽  
Wenxia Yang ◽  
...  
Keyword(s):  
Catalytic Activity ◽  
Fatty Acid ◽  
Directed Evolution ◽  
High Throughput ◽  
High Throughput Screening ◽  
Colorimetric Detection ◽  
Screening Method ◽  
Random Mutagenesis ◽  
Direct Production ◽  
Consumption Activity

P450 fatty acid decarboxylases (FADCs) have recently been attracting considerable attention owing to their one-step direct production of industrially important 1-alkenes from biologically abundant feedstock free fatty acids under mild conditions. However, attempts to improve the catalytic activity of FADCs have met with little success. Protein engineering has been limited to selected residues and small mutant libraries due to lack of an effective high-throughput screening (HTS) method. Here, we devise a catalase-deficient <i>Escherichia coli</i> host strain and report an HTS approach based on colorimetric detection of H<sub>2</sub>O<sub>2</sub>-consumption activity of FADCs. Directed evolution enabled by this method has led to effective identification for the first time of improved FADC variants for medium-chain 1-alkene production from both DNA shuffling and random mutagenesis libraries. Advantageously, this screening method can be extended to other enzymes that stoichiometrically utilize H<sub>2</sub>O<sub>2</sub> as co-substrate.

High-throughput colorimetric assays for mercury(ii) in blood and wastewater based on the mercury-stimulated catalytic activity of small silver nanoparticles in a temperature-switchable gelatin matrix

2014 ◽  
Vol 50 (65) ◽  
pp. 9196-9199 ◽  
Author(s):  
Zongzhao Sun ◽  
Ning Zhang ◽  
Yanmei Si ◽  
Shuai Li ◽  
Jiangwei Wen ◽  
...  
Keyword(s):  
Silver Nanoparticles ◽  
Catalytic Activity ◽  
High Throughput ◽  
Gelatin Matrix ◽  
Colorimetric Assays

Colorimetric mercury(ii) assays with 96-cell plates were achieved by the mercury-stimulated catalytic activity of small silver nanoparticles in switchable gelatin.

scholarly journals Preparation of Metal Oxides Containing ppm Levels of Pd as Catalysts for the Reduction of Nitroarene and Evaluation of Their Catalytic Activity by the Fluorescence-Based High-Throughput Screening Method

Catalysts ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 542
Author(s):  
Taeho Lim ◽  
Min Su Han
Keyword(s):  
Catalytic Activity ◽  
Metal Oxides ◽  
High Throughput ◽  
High Throughput Screening ◽  
Screening Method ◽  
Reduction Reaction ◽  
Precipitation Method ◽  
Reaction Conditions ◽  
One Pot ◽  
Co Precipitation

Herein, an easily accessible and efficient green method for the reduction of nitroarene compounds was developed using metal oxide catalysts. Heterogeneous metal oxides with or without Pd were prepared by a simple and scalable co-precipitation method and used for the reduction of nitroarenes. A fluorescence-based high-throughput screening (HTS) method was also developed for the rapid analysis of the reaction conditions. The catalytic activity of the metal oxides and reaction conditions were rapidly screened by the fluorescence-based HTS method, and Pd/CuO showed the highest catalytic activity under mild reaction conditions. After identifying the optimal reaction conditions, various nitroarenes were reduced to the corresponding aniline derivatives by Pd/CuO (0.005 mol% of Pd) under these conditions. Furthermore, the Pd/CuO catalyst was used for the one-pot Suzuki–Miyaura cross-coupling/reduction reaction. A gram-scale reaction (20 mmol) was successfully performed using the present method, and Pd/CuO showed high reusability without a loss of catalytic activity for five cycles.

Infrared Thermography as a High-Throughput Tool in Catalysis Research

2012 ◽  
Vol 14 (5) ◽  
pp. 295-303 ◽  
Author(s):  
Jonas Loskyll ◽  
Klaus Stoewe ◽  
Wilhelm F. Maier
Keyword(s):  
Infrared Thermography ◽  
High Throughput ◽  
Catalysis Research

scholarly journals An Efficient Discovery of Active, Selective and Stable Catalysts for Electrochemical H2O2 Synthesis Through Active Motif Screening

2020 ◽  
Author(s):  
Seoin Back ◽  
Jonggeol Na ◽  
Zachary Ulissi
Keyword(s):  
Catalytic Activity ◽  
Dft Calculations ◽  
Electrochemical Reduction ◽  
High Throughput ◽  
High Throughput Screening ◽  
Density Functional ◽  
H2o2 Production ◽  
High Catalytic Activity ◽  
Adsorption Sites ◽  
O2 Reduction

<div> <div> <div> <p>Electrochemical reduction of O2 provides a clean and decentralized pathway to produce H2O2 compared to the current energy-intensive anthraquinone process. As the electrochemical reduction of O2 proceeds via either two-electron or four-electron path- way, it is thus essential to control the selectivity as well as to maximize the catalytic activity. Siahrostami et al. demonstrated a novel approach to control the reaction pathway by optimizing an adsorption ensemble to tune adsorption sites of reaction intermediates, and identified Pt-Hg catalysts from density functional theory (DFT) calculations and experimentally validated this catalyst (Nat. Mater. 2013, 12, 1137). Inspired by this concept, in this work, we apply a state-of-the-art high-throughput screening to develop O2 reduction catalyst for selective H2O2 production. Starting from Materials Project database, we evaluate activity, selectivity and electrochemical stability. To efficiently perform the screening, we introduce an active motif based approach which pre-screens unpromising materials and only performs DFT calculations for promising materials, which significantly reduce the number of the required calculations. We not only provide a list of promising candidates identified by DFT calculations, but also suggest element species to achieve high catalytic activity or H2O2 selectivity for future experimental attempts. Finally, we discuss a strategy for efficient future high-throughput screening using a machine learning pipeline consisting of a non-linear dimension reduction and a density-based clustering. </p> </div> </div> </div>

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